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A Tool for Subjective and Interactive Visual Data Exploration Read chapter Read first chapter

2016 | OriginalPaper | Chapter

SITS-P2miner: Pattern-Based Mining of Satellite Image Time Series

Authors : Tuan Nguyen, Nicolas Méger, Christophe Rigotti, Catherine Pothier, Rémi Andreoli

Published in: Machine Learning and Knowledge Discovery in Databases

Publisher: Springer International Publishing

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Abstract

This paper presents a mining system for extracting patterns from Satellite Image Time Series. This system is a fully-fledged tool comprising four main modules for pre-processing, pattern extraction, pattern ranking and pattern visualization. It is based on the extraction of grouped frequent sequential patterns and on swap randomization.

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Literature
1.
Agrawal, R., Srikant, R.: Mining sequential patterns. In: Proceedings of Conference ICDE, pp. 3–14 (1995)
2.
Gueguen, L., Datcu, M.: Image time-series data mining based on the information-bottleneck principle. IEEE Trans. Geosci. Remote Sens. 45(4), 827–838 (2007)CrossRef
3.
Honda, R., Konishi, O.: Temporal rule discovery for time-series satellite images and integration with RDB. In: Siebes, A., De Raedt, L. (eds.) PKDD 2001. LNCS (LNAI), vol. 2168, pp. 204–215. Springer, Heidelberg (2001)CrossRef
4.
Julea, A., Méger, N., Bolon, P., Rigotti, C., Doin, M.P., Lasserre, C., Trouvé, E., Lăzărescu, V.N.: Unsupervised spatiotemporal mining of satellite image time series using grouped frequent sequential patterns. IEEE Trans. Geosci. Remote Sens. 49(4), 1417–1430 (2011)CrossRef
5.
Méger, N., Rigotti, C., Pothier, C.: Swap randomization of bases of sequences for mining satellite image times series. In: Appice, A., Rodrigues, P.P., Santos Costa, V., Gama, J., Jorge, A., Soares, C. (eds.) ECML PKDD 2015. LNCS, vol. 9285, pp. 190–205. Springer, Heidelberg (2015)CrossRef
Metadata
Title
SITS-P2miner: Pattern-Based Mining of Satellite Image Time Series
Authors
Tuan Nguyen
Nicolas Méger
Christophe Rigotti
Catherine Pothier
Rémi Andreoli
Copyright Year
2016
Book
Machine Learning and Knowledge Discovery in Databases

Print ISBN: 978-3-319-46130-4

Electronic ISBN: 978-3-319-46131-1

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-46131-1_14

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